xVP Maven, Early Stage Marketing Leader

Marketing leaders must give their team what they need to understand the market, the customer and the bigger why.
Now we have a new kind of team member: AI.
AI is capable of limitless execution work but cannot feel what your customer does. It cannot infer the experience of a busy day in a tired body, with the radio on and a kid in the back seat. It does not intuitively understand the motivations and hesitations that come from an inner world of hopes and fears.
I've built a method to close that gap and give AI what it needs to execute marketing well. It is pulled from a multi-disciplinary career in early-stage marketing leadership, as well as my life-long need to understand human behavior as an neurodiverse individual.
It uses frameworks from brand strategy and behavioral psychology to UX. Frameworks that exist to make sense of and synthesize human complexity. Tested and refined for a new application: AI context engineering for marketing.
It delivers a structured account of your customer's lived temporal and emotional experience, in every dimension that is actionable for marketing decisions.
And once done, it's impact scales in lockstep with your AI.
🔥 JUNE BETA ENROLL: USE CODE BETA500
I'll guide you through a rigorous, business-specific context engineering process. All the tacit knowledge you hold will become AI-legible.
Define the conversation your offer is naturally part of, name the cultural position it takes
Pin down what your offer stands for in a changing world, articulate what it moves towards, and away from
Create AI context that captures what most people think of as intangible using tools from the fields of Cultural Foresight & Sense-Making
Structure temporal information using the journey mapping practice used in User Experience design
Capture what your customer feels and fears at each stage using Behavioral Psychology, the study of how people really decide.
Create AI context that holds the human experience AI needs to access to fully understand the marketing funnel
Use Porter's Five Forces, the classic framework for what actually pressures a market
Apply the Jobs-to-be-Done approach, to name the real job your customer needs done and bring your value proposition to life
Create AI context that models customer needs and competitive forces into a world-picture AI can't otherwise grasp
Name you brand's personality archetype, give AI a consistent character to act from
Define your brands interpersonal posture and the relationship you are building, so the AI's tone and choices are deliberate
Encode operational guardrails: what your brand would never do, say, think, along with WHY.
Define your unique point of view and the content pillars that will make it travel online
Encode your authentic voice, and what makes it real and relatable
Create AI context for the new media landscape where para-social networks make individuals the most powerful marketing vector

Product Marketing Leader I AI-Qual & Design Research
Growth & GTM Engineers: Your AI-stack is deployed at scale. A source-of-truth for your marketing context will have massive leverage.
Marketing Team Leaders: The buck stops with you and right now you see AI experiments causing brand chaos across a growing surface area.
"Team of One" Operators: Marketing is just one of your many jobs, and you need your AI-team to deliver quality work you don't need to redo.
You don't have to be a marketer, but you must have a marketing execution mandate and a strong understanding of your offer
You don't have to be an advanced AI user, but you must be excited to use AI, and have a real application for it.

Live sessions
Learn directly from Vanina Schick in a real-time, interactive format.
Lifetime access
Go back to course content and recordings whenever you need to.
Community of peers
Stay accountable and share insights with like-minded professionals.
Certificate of completion
Share your new skills with your employer or on LinkedIn.
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Jun
15
Cultural Context
Jun
16
Customer Journey
Jun
17
Competitive Environment
Jun
18
Brand
Jun
19
Storytelling
Jun
22
Engineer your context
Jun
26
Demo how you used your context
Live sessions
5 hrs
5 days. 5 modules. 1 hour live together Monday - Friday.
Mon, Jun 15
3:00 PM—4:00 PM (UTC)
Tue, Jun 16
3:00 PM—4:00 PM (UTC)
Wed, Jun 17
3:00 PM—4:00 PM (UTC)
Post-session work
5 hrs
After every live session, apply the framework to your product and audience, and build up your own unique context file in a structured, guided process.
Personal project & live demo session
5 hrs
After the weeks work, test your new context file in a real AI application. Demo your output in our final session on the second Monday.
PSA: This course sits upstream of AI execution, it doesn't teach tool use.
Across all major AI labs and tool platforms, there's one consensus: AI output quality depends on context.
The diagnosis is right. It is also the part neither the the labs nor the tools can do for you. Context is irreducibly use-case-specific. Better models will not hold what you know about your buyer. A tool will not author your brief for you. An agency rents you their judgment for a quarter and builds you nothing you keep. This course is the solution.
The output is your use-case specific context, encoded for AI to use. You will build a large context file that will be relevant for all tools that takes a context document or system prompt: Claude, ChatGPT, Perplexity, custom GPTs, your own agent stack.
In week one we'll build your context, focusing on the strategic knowledge you need your context to hold. This is upstream from AI work.
In week two you will apply and demo your content AI execution work. This can be as simple as content writing using an AI chat, or as technical as building an advanced GTM automation. The course will not teach you application, but you can expect to learn a lot from other participants.
PSA: Context engineering is an emerging field. This is frontier work.
As far as I know, the methodology I share in this course is the most advanced work in the space of context engineering for marketing.
Some of it is proven and works consistently. Some of it is well-evidenced conviction that needs further testing across a wider range of applications and marketing contexts. That is the natural limit of individual practitioner research.
So I'm choosing to build-in-public. This is a lab as much as a course. Participants will benefit from my methodology and contribute to it.
If you want a locked, final system, this is not it yet.
If you want to be among the first to build this capability, this is exactly it. The practitioners who master it now hold an advantage that will compound.
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